View source: R/calc_relative_var.R
calc_relative_var | R Documentation |
Calculates relative bias, mean squared error (relative mse), and root mean squared error (relative rmse) of variance estimators. The function also calculates the associated jack-knife Monte Carlo standard errors.
calc_relative_var(
data,
estimates,
var_estimates,
criteria = c("relative bias", "relative mse", "relative rmse"),
winz = Inf,
var_winz = winz
)
data |
data frame or tibble containing the simulation results. |
estimates |
vector or name of column from |
var_estimates |
vector or name of column from |
criteria |
character or character vector indicating the performance
criteria to be calculated, with possible options |
winz |
numeric value for winsorization constant. If set to a finite
value, estimates will be winsorized at the constant multiple of the
inter-quartile range below the 25th percentile or above the 75th percentile
of the distribution. For instance, setting |
var_winz |
numeric value for winsorization constant for the
variance estimates. If set to a finite value, variance estimates will be
winsorized at the constant multiple of the inter-quartile range below the
25th percentile or above the 75th percentile of the distribution. For
instance, setting |
A tibble containing the number of simulation iterations, performance criteria estimate(s) and the associated MCSE.
calc_relative_var(data = alpha_res, estimates = A, var_estimates = Var_A)
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